Analysis
Helia Hosseinpour, Laura E. Matzen, Kristin M. Divis, Spencer C. Castro, and Lace Padilla
2023-05-08
Experiment 1
Theme used for every small multiple created
Demographics
There were 141 participants in Experiments 1. There were 71 participants who selected Male, 65 participants who selected Female, 4 participants who selected Non-binary / third gender, and 1 who selected Prefer not to say.
the mean age is 33.62 (SD = 11.79).
Identify
Identify 1 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfaccID1
##
## AIC BIC logLik deviance df.resid
## 5435.4 5463.0 -2713.7 5427.4 7196
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -9.0805 0.1872 0.3013 0.4392 1.7572
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.1257 0.3545
## ResponseId (Intercept) 0.6604 0.8126
## Number of obs: 7200, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.978545 0.216501 13.76 <2e-16 ***
## Frame_Quantity -0.025610 0.001765 -14.51 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.354
Identify 2 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfaccID2
##
## AIC BIC logLik deviance df.resid
## 8946.3 8973.9 -4469.2 8938.3 7195
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.4002 -1.0219 0.5581 0.7840 5.0077
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.08608 0.2934
## ResponseId (Intercept) 0.73647 0.8582
## Number of obs: 7199, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.621800 0.209498 2.968 0.003 **
## Frame_Quantity -0.010049 0.001236 -8.128 4.35e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.216
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?
Identify 2 Secondary Analysis (MeanRange vs Range vs Mean)
Identify 2 Mean Accuracy
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 8962.1 8989.6 -4477.0 8954.1 7195
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.7411 -0.9203 0.4836 0.8070 4.8492
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.1318 0.3631
## ResponseId (Intercept) 0.5506 0.7420
## Number of obs: 7199, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.855632 0.192121 4.454 8.44e-06 ***
## Frame_Quantity -0.019823 0.001254 -15.806 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.239
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Identify 2 Range Accuracy
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 8503.5 8531.0 -4247.7 8495.5 7195
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.8554 -0.7200 -0.4952 0.9845 4.9350
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.2768 0.5261
## ResponseId (Intercept) 0.4440 0.6663
## Number of obs: 7199, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -0.326442 0.196937 -1.658 0.0974 .
## Frame_Quantity -0.012962 0.001282 -10.109 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.222
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Plots side-by-side
Identify 3 Accuracy Analysis
We have a problem Trial for 18 frames - trial 12 (letter N) frame 14 is visually not over the dotted line at 79.5, but the value is 79.507. We are marking this as not a correct response.
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfaccID3
##
## AIC BIC logLik deviance df.resid
## 4231.1 4258.7 -2111.6 4223.1 7196
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.5642 0.1691 0.2344 0.3401 1.8523
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.1315 0.3626
## ResponseId (Intercept) 0.9624 0.9810
## Number of obs: 7200, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.083477 0.253215 12.177 < 2e-16 ***
## Frame_Quantity -0.015580 0.002004 -7.776 7.49e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.326
Compare
Compare 1 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfaccC1
##
## AIC BIC logLik deviance df.resid
## 3736.7 3764.2 -1864.3 3728.7 7196
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.5995 0.1668 0.2247 0.3047 1.3897
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.2774 0.5267
## ResponseId (Intercept) 0.5393 0.7343
## Number of obs: 7200, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.29076 0.22765 14.455 < 2e-16 ***
## Frame_Quantity -0.01481 0.00217 -6.824 8.86e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.394
Compare 2 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfaccC2
##
## AIC BIC logLik deviance df.resid
## 8976.4 9003.9 -4484.2 8968.4 7196
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.4039 -1.2057 0.5978 0.7196 1.2085
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.10190 0.3192
## ResponseId (Intercept) 0.05453 0.2335
## Number of obs: 7200, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.899303 0.102535 8.771 < 2e-16 ***
## Frame_Quantity -0.004630 0.001229 -3.768 0.000164 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.439
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?
Compare 2 Secondary Analysis (MeanRange vs Range vs Mean)
Compare 2 Mean Accuracy
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 5713.7 5741.2 -2852.8 5705.7 7196
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -5.3483 0.2819 0.3506 0.4224 1.5838
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.1558 0.3948
## ResponseId (Intercept) 0.2572 0.5072
## Number of obs: 7200, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.242099 0.161865 13.852 < 2e-16 ***
## Frame_Quantity -0.009852 0.001662 -5.926 3.1e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.400Compare 2 Range Accuracy
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 179328.0 179367.1 -89660.0 179320.0 129596
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.1752 -0.9982 -0.8981 1.0005 1.1142
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.01244 0.1115
## ResponseId (Intercept) 0.00000 0.0000
## Number of obs: 129600, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.0009688 0.0272774 0.036 0.972
## Frame_Quantity -0.0003051 0.0002681 -1.138 0.255
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.353
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')Plots side-by-side
Summarize
Summarize 1 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfaccS1
##
## AIC BIC logLik deviance df.resid
## 9927.3 9955.0 -4959.6 9919.3 7556
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.2132 -1.1414 0.6558 0.7954 1.4134
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.07272 0.2697
## Trial (Intercept) 0.04854 0.2203
## Number of obs: 7560, groups: ResponseId, 21; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.740427 0.091000 8.137 4.07e-16 ***
## Frame_Quantity -0.007375 0.001159 -6.362 2.00e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.468
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?
Summarize 2 Error Analysis
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: error ~ Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: dfaccS2
##
## REML criterion at convergence: 210.1
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -4.2895 -0.5816 -0.1634 0.3995 7.3860
##
## Random effects:
## Groups Name Variance Std.Dev.
## Trial (Intercept) 0.0006717 0.02592
## ResponseId (Intercept) 0.0730537 0.27028
## Residual 0.0588751 0.24264
## Number of obs: 7144, groups: Trial, 20; ResponseId, 20
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 2.241e-01 6.099e-02 1.960e+01 3.675 0.00154 **
## Frame_Quantity 2.507e-03 1.385e-04 7.104e+03 18.107 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr)
## Frame_Qntty -0.082
Experiment 1 - 6 Combined Tasks of Accuracy
Combine all of the main accuracy datasets
Changing the referent
Identify 1
(Spencer can you update the FullModels.RData with these interation models?)
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ task * Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: df_full
##
## AIC BIC logLik deviance df.resid
## 41537.5 41659.1 -20754.8 41509.5 43545
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.4240 -0.2028 0.2946 0.6452 4.8237
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.4705 0.6859
## Trial (Intercept) 0.0371 0.1926
## Number of obs: 43559, groups: ResponseId, 121; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.926641 0.180509 16.213 < 2e-16 ***
## taskID2 -2.309450 0.238835 -9.670 < 2e-16 ***
## taskID3 0.088089 0.251002 0.351 0.725627
## taskComp1 0.254216 0.253828 1.002 0.316570
## taskComp2 -2.035927 0.238525 -8.535 < 2e-16 ***
## taskSumm1 -2.184943 0.235676 -9.271 < 2e-16 ***
## Frame_Quantity -0.025227 0.001751 -14.403 < 2e-16 ***
## taskID2:Frame_Quantity 0.015302 0.002139 7.153 8.5e-13 ***
## taskID3:Frame_Quantity 0.009926 0.002650 3.746 0.000180 ***
## taskComp1:Frame_Quantity 0.010761 0.002775 3.879 0.000105 ***
## taskComp2:Frame_Quantity 0.020638 0.002136 9.660 < 2e-16 ***
## taskSumm1:Frame_Quantity 0.017839 0.002101 8.491 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tskID2 tskID3 tskCm1 tskCm2 tskSm1 Frm_Qn tID2:F tID3:F
## taskID2 -0.713
## taskID3 -0.676 0.511
## taskComp1 -0.670 0.506 0.480
## taskComp2 -0.714 0.540 0.512 0.507
## taskSumm1 -0.722 0.547 0.518 0.513 0.547
## Frame_Qntty -0.418 0.316 0.300 0.297 0.316 0.320
## tskID2:Fr_Q 0.342 -0.367 -0.246 -0.243 -0.259 -0.262 -0.819
## tskID3:Fr_Q 0.275 -0.208 -0.441 -0.196 -0.208 -0.211 -0.660 0.541
## tskCmp1:F_Q 0.264 -0.199 -0.189 -0.457 -0.199 -0.202 -0.631 0.517 0.417
## tskCmp2:F_Q 0.343 -0.259 -0.246 -0.243 -0.367 -0.263 -0.820 0.671 0.541
## tskSmm1:F_Q 0.349 -0.264 -0.250 -0.248 -0.264 -0.367 -0.834 0.682 0.551
## tC1:F_ tC2:F_
## taskID2
## taskID3
## taskComp1
## taskComp2
## taskSumm1
## Frame_Qntty
## tskID2:Fr_Q
## tskID3:Fr_Q
## tskCmp1:F_Q
## tskCmp2:F_Q 0.517
## tskSmm1:F_Q 0.526 0.683
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Identify 2
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ task * Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: df_full
##
## AIC BIC logLik deviance df.resid
## 41537.5 41659.1 -20754.8 41509.5 43545
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.4240 -0.2028 0.2946 0.6452 4.8235
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.47048 0.6859
## Trial (Intercept) 0.03709 0.1926
## Number of obs: 43559, groups: ResponseId, 121; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.617207 0.167590 3.683 0.000231 ***
## taskID1 2.309442 0.238647 9.677 < 2e-16 ***
## taskID3 2.397529 0.242511 9.886 < 2e-16 ***
## taskComp1 2.563595 0.244978 10.465 < 2e-16 ***
## taskComp2 0.273475 0.228933 1.195 0.232257
## taskSumm1 0.124513 0.225900 0.551 0.581507
## Frame_Quantity -0.009924 0.001229 -8.078 6.58e-16 ***
## taskID1:Frame_Quantity -0.015303 0.002139 -7.153 8.46e-13 ***
## taskID3:Frame_Quantity -0.005377 0.002339 -2.299 0.021497 *
## taskComp1:Frame_Quantity -0.004542 0.002478 -1.833 0.066852 .
## taskComp2:Frame_Quantity 0.005335 0.001734 3.077 0.002091 **
## taskSumm1:Frame_Quantity 0.002536 0.001690 1.501 0.133466
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tskID1 tskID3 tskCm1 tskCm2 tskSm1 Frm_Qn tID1:F tID3:F
## taskID1 -0.655
## taskID3 -0.646 0.454
## taskComp1 -0.639 0.449 0.442
## taskComp2 -0.684 0.480 0.473 0.468
## taskSumm1 -0.693 0.486 0.479 0.474 0.507
## Frame_Qntty -0.268 0.188 0.185 0.183 0.196 0.199
## tskID1:Fr_Q 0.154 -0.367 -0.106 -0.105 -0.113 -0.114 -0.574
## tskID3:Fr_Q 0.141 -0.099 -0.384 -0.097 -0.103 -0.105 -0.525 0.302
## tskCmp1:F_Q 0.133 -0.093 -0.092 -0.404 -0.097 -0.098 -0.496 0.285 0.260
## tskCmp2:F_Q 0.190 -0.133 -0.131 -0.130 -0.277 -0.141 -0.709 0.407 0.372
## tskSmm1:F_Q 0.195 -0.137 -0.135 -0.133 -0.143 -0.274 -0.727 0.417 0.382
## tC1:F_ tC2:F_
## taskID1
## taskID3
## taskComp1
## taskComp2
## taskSumm1
## Frame_Qntty
## tskID1:Fr_Q
## tskID3:Fr_Q
## tskCmp1:F_Q
## tskCmp2:F_Q 0.351
## tskSmm1:F_Q 0.360 0.515
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.00231823 (tol = 0.002, component 1)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Identify 3
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ task * Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: df_full
##
## AIC BIC logLik deviance df.resid
## 41537.5 41659.1 -20754.8 41509.5 43545
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.4233 -0.2028 0.2946 0.6452 4.8228
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.47035 0.6858
## Trial (Intercept) 0.03712 0.1927
## Number of obs: 43559, groups: ResponseId, 121; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.0153666 0.1844898 16.344 < 2e-16 ***
## taskID2 -2.3976679 0.2416294 -9.923 < 2e-16 ***
## taskID1 -0.0885235 0.2505179 -0.353 0.723817
## taskComp1 0.1666895 0.2564984 0.650 0.515779
## taskComp2 -2.1239708 0.2413664 -8.800 < 2e-16 ***
## taskSumm1 -2.2739871 0.2384072 -9.538 < 2e-16 ***
## Frame_Quantity -0.0153273 0.0019883 -7.709 1.27e-14 ***
## taskID2:Frame_Quantity 0.0054103 0.0023370 2.315 0.020607 *
## taskID1:Frame_Quantity -0.0098952 0.0026490 -3.735 0.000187 ***
## taskComp1:Frame_Quantity 0.0008612 0.0029294 0.294 0.768767
## taskComp2:Frame_Quantity 0.0107367 0.0023343 4.600 4.23e-06 ***
## taskSumm1:Frame_Quantity 0.0079384 0.0023018 3.449 0.000563 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tskID2 tskID1 tskCm1 tskCm2 tskSm1 Frm_Qn tID2:F tID1:F
## taskID2 -0.722
## taskID1 -0.695 0.530
## taskComp1 -0.678 0.518 0.499
## taskComp2 -0.722 0.551 0.530 0.518
## taskSumm1 -0.730 0.558 0.537 0.524 0.558
## Frame_Qntty -0.438 0.335 0.322 0.315 0.335 0.339
## tskID2:Fr_Q 0.373 -0.382 -0.274 -0.268 -0.285 -0.288 -0.851
## tskID1:Fr_Q 0.328 -0.250 -0.440 -0.236 -0.251 -0.254 -0.750 0.638
## tskCmp1:F_Q 0.297 -0.227 -0.218 -0.466 -0.227 -0.229 -0.678 0.577 0.509
## tskCmp2:F_Q 0.373 -0.285 -0.274 -0.268 -0.382 -0.288 -0.852 0.725 0.639
## tskSmm1:F_Q 0.378 -0.289 -0.278 -0.272 -0.289 -0.382 -0.864 0.735 0.648
## tC1:F_ tC2:F_
## taskID2
## taskID1
## taskComp1
## taskComp2
## taskSumm1
## Frame_Qntty
## tskID2:Fr_Q
## tskID1:Fr_Q
## tskCmp1:F_Q
## tskCmp2:F_Q 0.578
## tskSmm1:F_Q 0.586 0.736
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.084662 (tol = 0.002, component 1)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Compare 1
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ task * Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: df_fullComp1
##
## AIC BIC logLik deviance df.resid
## 41537.5 41659.1 -20754.8 41509.5 43545
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.4246 -0.2028 0.2946 0.6452 4.8234
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.47052 0.6859
## Trial (Intercept) 0.03712 0.1927
## Number of obs: 43559, groups: ResponseId, 121; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.1810070 0.1890382 16.827 < 2e-16 ***
## taskID1 -0.2538107 0.2542411 -0.998 0.318131
## taskID2 -2.5639430 0.2453331 -10.451 < 2e-16 ***
## taskID3 -0.1664023 0.2573577 -0.647 0.517904
## taskComp2 -2.2901026 0.2452509 -9.338 < 2e-16 ***
## taskSumm1 -2.4388968 0.2422743 -10.067 < 2e-16 ***
## Frame_Quantity -0.0144732 0.0021529 -6.723 1.78e-11 ***
## taskID1:Frame_Quantity -0.0107568 0.0027755 -3.876 0.000106 ***
## taskID2:Frame_Quantity 0.0045532 0.0024788 1.837 0.066232 .
## taskID3:Frame_Quantity -0.0008266 0.0029312 -0.282 0.777937
## taskComp2:Frame_Quantity 0.0098860 0.0024764 3.992 6.55e-05 ***
## taskSumm1:Frame_Quantity 0.0070830 0.0024457 2.896 0.003778 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tskID1 tskID2 tskID3 tskCm2 tskSm1 Frm_Qn tID1:F tID2:F
## taskID1 -0.705
## taskID2 -0.731 0.543
## taskID3 -0.695 0.517 0.536
## taskComp2 -0.732 0.544 0.564 0.536
## taskSumm1 -0.740 0.550 0.571 0.542 0.571
## Frame_Qntty -0.468 0.348 0.361 0.343 0.361 0.365
## tskID1:Fr_Q 0.363 -0.458 -0.280 -0.267 -0.280 -0.283 -0.776
## tskID2:Fr_Q 0.407 -0.302 -0.404 -0.298 -0.314 -0.317 -0.869 0.674
## tskID3:Fr_Q 0.343 -0.256 -0.265 -0.467 -0.265 -0.268 -0.734 0.570 0.638
## tskCmp2:F_Q 0.407 -0.303 -0.314 -0.299 -0.405 -0.318 -0.869 0.674 0.755
## tskSmm1:F_Q 0.412 -0.306 -0.318 -0.302 -0.318 -0.405 -0.880 0.683 0.765
## tID3:F tC2:F_
## taskID1
## taskID2
## taskID3
## taskComp2
## taskSumm1
## Frame_Qntty
## tskID1:Fr_Q
## tskID2:Fr_Q
## tskID3:Fr_Q
## tskCmp2:F_Q 0.638
## tskSmm1:F_Q 0.646 0.765
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.0296081 (tol = 0.002, component 1)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Compare 2
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ task * Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: df_fullComp2
##
## AIC BIC logLik deviance df.resid
## 41537.5 41659.1 -20754.8 41509.5 43545
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.4239 -0.2028 0.2946 0.6452 4.8236
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.47049 0.6859
## Trial (Intercept) 0.03709 0.1926
## Number of obs: 43559, groups: ResponseId, 121; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.890699 0.167414 5.320 1.04e-07 ***
## taskComp1 2.290170 0.244947 9.350 < 2e-16 ***
## taskID1 2.035940 0.238651 8.531 < 2e-16 ***
## taskID2 -0.273509 0.228966 -1.195 0.232267
## taskID3 2.124025 0.242176 8.771 < 2e-16 ***
## taskSumm1 -0.148949 0.225642 -0.660 0.509181
## Frame_Quantity -0.004590 0.001223 -3.752 0.000176 ***
## taskComp1:Frame_Quantity -0.009877 0.002476 -3.989 6.62e-05 ***
## taskID1:Frame_Quantity -0.020637 0.002137 -9.659 < 2e-16 ***
## taskID2:Frame_Quantity -0.005334 0.001734 -3.077 0.002092 **
## taskID3:Frame_Quantity -0.010711 0.002336 -4.585 4.53e-06 ***
## taskSumm1:Frame_Quantity -0.002799 0.001686 -1.660 0.096870 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tskCm1 tskID1 tskID2 tskID3 tskSm1 Frm_Qn tC1:F_ tID1:F
## taskComp1 -0.639
## taskID1 -0.655 0.448
## taskID2 -0.683 0.467 0.479
## taskID3 -0.645 0.442 0.453 0.472
## taskSumm1 -0.692 0.473 0.485 0.506 0.478
## Frame_Qntty -0.268 0.183 0.188 0.196 0.185 0.198
## tskCmp1:F_Q 0.132 -0.404 -0.093 -0.097 -0.092 -0.098 -0.494
## tskID1:Fr_Q 0.153 -0.105 -0.367 -0.112 -0.106 -0.114 -0.573 0.283
## tskID2:Fr_Q 0.189 -0.129 -0.133 -0.277 -0.131 -0.140 -0.706 0.349 0.404
## tskID3:Fr_Q 0.140 -0.096 -0.098 -0.102 -0.384 -0.104 -0.524 0.259 0.300
## tskSmm1:F_Q 0.194 -0.133 -0.136 -0.142 -0.134 -0.274 -0.726 0.359 0.415
## tID2:F tID3:F
## taskComp1
## taskID1
## taskID2
## taskID3
## taskSumm1
## Frame_Qntty
## tskCmp1:F_Q
## tskID1:Fr_Q
## tskID2:Fr_Q
## tskID3:Fr_Q 0.370
## tskSmm1:F_Q 0.512 0.380
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Summarize 1
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ task * Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: df_fullSumm1
##
## AIC BIC logLik deviance df.resid
## 41537.5 41659.1 -20754.8 41509.5 43545
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -7.4240 -0.2028 0.2946 0.6452 4.8236
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.4705 0.6859
## Trial (Intercept) 0.0371 0.1926
## Number of obs: 43559, groups: ResponseId, 121; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.741674 0.163324 4.541 5.60e-06 ***
## taskComp1 2.439180 0.242014 10.079 < 2e-16 ***
## taskID1 2.184915 0.235692 9.270 < 2e-16 ***
## taskID2 -0.124482 0.226180 -0.550 0.582069
## taskID3 2.273063 0.239353 9.497 < 2e-16 ***
## taskComp2 0.149021 0.225788 0.660 0.509250
## Frame_Quantity -0.007389 0.001160 -6.368 1.92e-10 ***
## taskComp1:Frame_Quantity -0.007077 0.002445 -2.895 0.003796 **
## taskID1:Frame_Quantity -0.017838 0.002101 -8.490 < 2e-16 ***
## taskID2:Frame_Quantity -0.002536 0.001690 -1.501 0.133453
## taskID3:Frame_Quantity -0.007913 0.002304 -3.435 0.000592 ***
## taskComp2:Frame_Quantity 0.002799 0.001686 1.660 0.096897 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) tskCm1 tskID1 tskID2 tskID3 tskCm2 Frm_Qn tC1:F_ tID1:F
## taskComp1 -0.627
## taskID1 -0.644 0.435
## taskID2 -0.673 0.454 0.466
## taskID3 -0.635 0.429 0.440 0.459
## taskComp2 -0.673 0.454 0.466 0.486 0.459
## Frame_Qntty -0.261 0.176 0.181 0.189 0.178 0.189
## tskCmp1:F_Q 0.124 -0.404 -0.086 -0.089 -0.084 -0.089 -0.474
## tskID1:Fr_Q 0.144 -0.097 -0.367 -0.104 -0.098 -0.104 -0.552 0.262
## tskID2:Fr_Q 0.179 -0.121 -0.124 -0.274 -0.123 -0.130 -0.687 0.326 0.379
## tskID3:Fr_Q 0.131 -0.089 -0.091 -0.095 -0.384 -0.095 -0.504 0.239 0.278
## tskCmp2:F_Q 0.180 -0.121 -0.124 -0.130 -0.122 -0.274 -0.688 0.327 0.380
## tID2:F tID3:F
## taskComp1
## taskID1
## taskID2
## taskID3
## taskComp2
## Frame_Qntty
## tskCmp1:F_Q
## tskID1:Fr_Q
## tskID2:Fr_Q
## tskID3:Fr_Q 0.346
## tskCmp2:F_Q 0.473 0.347
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model failed to converge with max|grad| = 0.00422464 (tol = 0.002, component 1)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Plot of 7 tasks
Final Plot (ID1 & IDComp1 in pane 1, ID2 & Comp2 in pane 2, ID3 in pane 3, Summ1 in pane 4)
Means and SDs from df_full 6 tasks
## task
## ID2 S1 C2 ID1 ID3 C1
## 0.57 0.61 0.67 0.85 0.89 0.92## task
## C1 ID3 ID1 C2 S1 ID2
## 0.28 0.31 0.36 0.47 0.49 0.50## task
## ID1 ID2 ID3 C1 C2 S1
## 0.85 0.57 0.89 0.92 0.67 0.61## task
## ID1 ID2 ID3 C1 C2 S1
## 0.36 0.50 0.31 0.28 0.47 0.49## [1] 0.3091138## [1] 0.357361Means and SDs from df_full groups of Identify, Compare, and Summarize
## taskGroup
## Comp ID Summ
## 0.79 0.77 0.61## taskGroup
## Comp ID Summ
## 0.41 0.42 0.49Planned Comparison Groups (ID1 vs Comp1) - Testing for an Interaction
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ task * Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: df_ID1C1
##
## AIC BIC logLik deviance df.resid
## 9222.2 9267.6 -4605.1 9210.2 14394
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -8.5461 0.1835 0.2545 0.3718 1.6123
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.5867 0.7660
## Trial (Intercept) 0.1096 0.3311
## Number of obs: 14400, groups: ResponseId, 40; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.967874 0.205586 14.436 < 2e-16 ***
## taskC1 0.253019 0.276317 0.916 0.36
## Frame_Quantity -0.025531 0.001762 -14.488 < 2e-16 ***
## taskC1:Frame_Quantity 0.010933 0.002786 3.924 8.7e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) taskC1 Frm_Qn
## taskC1 -0.646
## Frame_Qntty -0.371 0.275
## tskC1:Frm_Q 0.234 -0.422 -0.632
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Planned Comparison Groups (ID2 vs Comp2) - Testing for an Interaction
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ task * Frame_Quantity + (1 | Trial) + (1 | ResponseId)
## Data: df_ID2C2
##
## AIC BIC logLik deviance df.resid
## 18014.4 18059.8 -9001.2 18002.4 14393
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.2492 -1.1198 0.5949 0.7465 4.5976
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.37314 0.6109
## Trial (Intercept) 0.05566 0.2359
## Number of obs: 14399, groups: ResponseId, 40; Trial, 20
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.621260 0.155443 3.997 6.42e-05 ***
## taskC2 0.272793 0.206637 1.320 0.1868
## Frame_Quantity -0.009947 0.001230 -8.087 6.13e-16 ***
## taskC2:Frame_Quantity 0.005340 0.001736 3.076 0.0021 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) taskC2 Frm_Qn
## taskC2 -0.665
## Frame_Qntty -0.289 0.218
## tskC2:Frm_Q 0.205 -0.308 -0.708
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## Model is nearly unidentifiable: very large eigenvalue
## - Rescale variables?Odds Ratios Confidence Intervals (> 1 increasing, < 1 decreasing the odds of a correct answer)
## Est LL UL
## (Intercept) 2.926641302 2.572843265 3.28043934
## taskID2 -2.309449797 -2.777566648 -1.84133295
## taskID3 0.088088608 -0.403875084 0.58005230
## taskComp1 0.254216174 -0.243286002 0.75171835
## taskComp2 -2.035926893 -2.503436659 -1.56841713
## taskSumm1 -2.184942847 -2.646867995 -1.72301770
## Frame_Quantity -0.025227165 -0.028660052 -0.02179428
## taskID2:Frame_Quantity 0.015302349 0.011109275 0.01949542
## taskID3:Frame_Quantity 0.009926002 0.004731854 0.01512015
## taskComp1:Frame_Quantity 0.010761169 0.005323149 0.01619919
## taskComp2:Frame_Quantity 0.020637618 0.016450361 0.02482487
## taskSumm1:Frame_Quantity 0.017838583 0.013720821 0.02195634## Est LL UL
## (Intercept) 18.66483555 13.10302691 26.5874510
## taskID2 0.09931588 0.06218965 0.1586059
## taskID3 1.09208489 0.66772753 1.7861318
## taskComp1 1.28945052 0.78404724 2.1206409
## taskComp2 0.13055941 0.08180338 0.2083748
## taskSumm1 0.11248416 0.07087284 0.1785266
## Frame_Quantity 0.97508838 0.97174675 0.9784415
## taskID2:Frame_Quantity 1.01542003 1.01117121 1.0196867
## taskID3:Frame_Quantity 1.00997543 1.00474307 1.0152350
## taskComp1:Frame_Quantity 1.01081928 1.00533734 1.0163311
## taskComp2:Frame_Quantity 1.02085205 1.01658641 1.0251356
## taskSumm1:Frame_Quantity 1.01799864 1.01381538 1.0221992Experiment 2
Demographics
There were 360 participants in Experiment 2. There were 171 participants who selected Male, 174 participants who selected Female, 10 participants who selected Non-binary/Third gender, and 2 who selected Prefer not to Say.
the mean age is 25.64 (SD = 15.4).
Identify
Identify 1 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + time_lim + scale + (1 | ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 1401.3 1428.8 -695.6 1391.3 1826
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.9443 0.1852 0.2570 0.3661 1.7518
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.9756 0.9877
## Number of obs: 1831, groups: ResponseId, 360
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.202246 0.216989 14.758 < 2e-16 ***
## Frame_Quantity -0.030608 0.002734 -11.197 < 2e-16 ***
## time_lim1 -0.556445 0.185541 -2.999 0.00271 **
## scaleFull 0.103310 0.183551 0.563 0.57354
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Frm_Qn tm_lm1
## Frame_Qntty -0.562
## time_lim1 -0.537 0.066
## scaleFull -0.415 -0.013 0.013## 2.5 % 97.5 %
## .sig01 NA NA
## (Intercept) 2.78 3.63
## Frame_Quantity -0.04 -0.03
## time_lim1 -0.92 -0.19
## scaleFull -0.26 0.46
Identify 2 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + time_lim + scale + (1 | ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 2313.6 2341.2 -1151.8 2303.6 1845
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.7894 -1.1293 0.5777 0.6439 1.5127
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 0.1439 0.3794
## Number of obs: 1850, groups: ResponseId, 360
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.171634 0.110223 10.630 <2e-16 ***
## Frame_Quantity -0.022735 0.002017 -11.274 <2e-16 ***
## time_lim1 -0.067559 0.109362 -0.618 0.537
## scaleFull -0.040458 0.109262 -0.370 0.711
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Frm_Qn tm_lm1
## Frame_Qntty -0.488
## time_lim1 -0.502 -0.009
## scaleFull -0.500 0.004 -0.002
Identify 3 Accuracy Analysis
We have a problem Trial for 18 frames - trial 12 (letter N) frame 14 is visually not over the dotted line at 79.5, but the value is 79.507. We are marking this as not a correct response.
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + time_lim + scale + (1 | Trial) + (1 |
## ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 1272.9 1305.8 -630.4 1260.9 1794
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.4827 0.0954 0.1911 0.3498 2.2059
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 1.976 1.406
## Trial (Intercept) 6.501 2.550
## Number of obs: 1800, groups: ResponseId, 360; Trial, 4
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 1.76474 1.32873 1.328 0.184131
## Frame_Quantity 0.04868 0.01251 3.890 0.000100 ***
## time_lim1 -1.36976 0.24667 -5.553 2.81e-08 ***
## scaleFull 0.83450 0.23210 3.595 0.000324 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Frm_Qn tm_lm1
## Frame_Qntty -0.208
## time_lim1 -0.113 -0.067
## scaleFull -0.066 0.038 -0.095## 2.5 % 97.5 %
## .sig01 NA NA
## .sig02 NA NA
## (Intercept) -0.84 4.37
## Frame_Quantity 0.02 0.07
## time_lim1 -1.85 -0.89
## scaleFull 0.38 1.29## scale
## Fixed Full
## 0.8066667 0.8811111## scale
## Fixed Full
## 0.3951317 0.3238377
Compare
Compare 1 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + time_lim + scale + (1 | Trial) + (1 |
## ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 324.4 357.4 -156.2 312.4 1795
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -6.2407 0.0021 0.0025 0.0177 4.8202
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 72.1012 8.4912
## Trial (Intercept) 0.6371 0.7982
## Number of obs: 1801, groups: ResponseId, 360; Trial, 4
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 13.9147 1.4249 9.766 < 2e-16 ***
## Frame_Quantity -0.0787 0.0140 -5.620 1.91e-08 ***
## time_lim1 -0.3832 0.9068 -0.423 0.673
## scaleFull 0.2101 0.9004 0.233 0.815
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Frm_Qn tm_lm1
## Frame_Qntty -0.677
## time_lim1 -0.359 0.000
## scaleFull -0.295 0.003 -0.005
Compare 2 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + time_lim + scale + (1 | Trial) + (1 |
## ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 1600.7 1633.8 -794.4 1588.7 1817
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.6522 0.1620 0.2645 0.4231 1.8475
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 2.3851 1.5444
## Trial (Intercept) 0.7794 0.8828
## Number of obs: 1823, groups: ResponseId, 360; Trial, 4
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 2.691799 0.492686 5.464 4.67e-08 ***
## Frame_Quantity -0.012656 0.003306 -3.828 0.000129 ***
## time_lim1 -0.253171 0.217055 -1.166 0.243457
## scaleFull -0.180190 0.216952 -0.831 0.406229
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Frm_Qn tm_lm1
## Frame_Qntty -0.155
## time_lim1 -0.231 0.004
## scaleFull -0.227 0.008 0.001
Summarize
Summarize 1 Accuracy Analysis
## Generalized linear mixed model fit by maximum likelihood (Laplace
## Approximation) [glmerMod]
## Family: binomial ( logit )
## Formula: acc ~ Frame_Quantity + time_lim + scale + (1 | ResponseId)
## Data: dfacc
##
## AIC BIC logLik deviance df.resid
## 2174.4 2201.9 -1082.2 2164.4 1788
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -1.6490 -1.4931 0.6255 0.6512 0.6991
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 4e-14 2e-07
## Number of obs: 1793, groups: ResponseId, 360
##
## Fixed effects:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 0.871067 0.101818 8.555 <2e-16 ***
## Frame_Quantity -0.002216 0.002047 -1.082 0.279
## time_lim1 0.085758 0.103939 0.825 0.409
## scaleFull 0.047924 0.103917 0.461 0.645
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Frm_Qn tm_lm1
## Frame_Qntty -0.485
## time_lim1 -0.499 0.002
## scaleFull -0.505 -0.002 -0.001
## optimizer (Nelder_Mead) convergence code: 0 (OK)
## boundary (singular) fit: see help('isSingular')
Summarize 2 Error Analysis
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: error ~ Frame_Quantity + time_lim + scale + (1 | Trial) + (1 |
## ResponseId)
## Data: dfacc
##
## REML criterion at convergence: 12614.2
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.1212 -0.4445 -0.0858 0.2524 7.8238
##
## Random effects:
## Groups Name Variance Std.Dev.
## ResponseId (Intercept) 15.165 3.894
## Trial (Intercept) 1.382 1.176
## Residual 54.999 7.416
## Number of obs: 1796, groups: ResponseId, 360; Trial, 3
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 1.668e+00 8.492e-01 4.053e+00 1.965 0.120
## Frame_Quantity 2.178e-01 8.043e-03 1.154e+03 27.075 <2e-16 ***
## time_lim1 7.795e-01 5.395e-01 3.576e+02 1.445 0.149
## scaleFull -3.375e-01 5.395e-01 3.576e+02 -0.626 0.532
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Frm_Qn tm_lm1
## Frame_Qntty -0.233
## time_lim1 -0.317 0.001
## scaleFull -0.318 0.001 0.000
Experiment 2 - 7 Tasks
Fixed vs Full Scale
Time Limit vs No Time Limit
